A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

What is strict aliasing? First we will describe what is aliasing and then we can learn what being strict about it means.

In C and C++ aliasing has to do with what expression types we are allowed to access stored values through. In both C and C++ the standard specifies which expression types are allowed to alias which types. The compiler and optimizer are allowed to assume we follow the aliasing rules strictly, hence the term strict aliasing rule. If we attempt to access a value using a type not allowed it is classified as undefined behavior(UB). Once we have undefined behavior all bets are off, the results of our program are no longer reliable.

Unfortunately with strict aliasing violations, we will often obtain the results we expect, leaving the possibility the a future version of a compiler with a new optimization will break code we th

See how a minor change to your commit message style can make a difference.

git commit -m"<type>(<optional scope>): <description>" \
  -m"<optional body>" \
  -m"<optional footer>"

This document describes the working setup for running the native Antigravity CLI (agy) on Android Termux.

The main goal is to run the official Linux ARM64 Antigravity binary directly from Termux without Cloud Shell, without a full VM, and without replacing Android. The setup uses a small binary patch plus a wrapper that adapts the Linux/glibc binary to Termux's Android environment.

The method is designed to be repeatable for future Antigravity releases. The patch script scans instruction patterns instead of relying on fixed offsets. If Antigravity changes its allocator code generation in the future, the script will print warning counts instead of silently claiming success.

Antigravity's Linux ARM64 binary can fail on Termux for multiple independent reasons.

TurkiyeAPI, Türkiye'nin illeri, ilçeleri, mahalleler ve köyler hakkında detaylı bilgiler sunan demografik ve coğrafi verilerle kapsamlı bir REST API'sidir.

API ana alan adı olarak turkiyeapi.dev kullanır. Ziyaret edebilirsiniz: https://turkiyeapi.dev

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A pattern for building personal knowledge bases using LLMs. Extended with lessons from building agentmemory 10K Stars ⭐️, a persistent memory engine for AI coding agents.

This builds on Andrej Karpathy's original LLM Wiki idea file. Everything in the original still applies. This document adds what we learned running the pattern in production: what breaks at scale, what's missing, and what separates a wiki that stays useful from one that rots.

Currently, Working on AKBP: Agent Knowledge Base Protocol based on my findings, a protocol for creating, updating, retrieving, and sharing durable knowledge across AI agents.